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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
NASA NTRS2000

The University of Nebraska at Omaha Center for Space Data Use in Teaching and Learning

Within the context of innovative coursework and other educational activities, we are proposing the establishment of a University of Nebraska at Omaha (UNO) Center for the Use of Space Data in Teaching and Learning. This Center will provide an exciting and motivating process for educators at all levels to become involved in professional development and training which engages real life applications of mathematics, science, and technology. The Center will facilitate innovative courses (including online and distance education formats), systematic degree programs, classroom research initiatives, new instructional methods and tools, engaging curriculum materials, and various symposiums. It will involve the active participation of several Departments and Colleges on the UNO campus and be well integrated into the campus environment. It will have a direct impact on pre-service and in-service educators, the K12 (kindergarten through 12th grade) students that they teach, and other college students of various science, mathematics, and technology related disciplines, in which they share coursework. It is our belief that there are many exciting opportunities represented by space data and imagery, as a context for engaging mathematics, science, and technology education. The UNO Center for Space Data Use in Teaching and Learning being proposed in this document will encompass a comprehensive training and dissemination strategy that targets the improvement of K-12 education, through changes in the undergraduate and graduate preparation of teachers in science, mathematics and technology education.

Grandgenett, Neal↗
NASA NTRS1990

Momentum harvesting techniques for solar system travel

Astronomers are lately estimating there are 400,000 Earth visiting asteroids larger than 100 meters in diameter. These asteroids are accessible sources of building materials, propellants, oxygen, water, and minerals which also constitute a huge momentum reserve, potentially usable for travel throughout the solar system. To use this momentum, these stealthy objects must be tracked and the extraction of the momentum wanted must be learned. Momentum harvesting by momentum transfer from asteroid to spacecraft, and by using the momentum of the extraterrestrial material to help deliver itself to the destination are discussed. A net and tether concept is the suggested means of asteroid capture, the basic momentum exchange process. The energy damping characteristics of the tether will determine the velocity mismatch that can be tolerated, and hence the amount of momentum that can be harvested per capture. As it plays out of its reel, drag on the tether steadily accelerates the spacecraft. A variety of concepts for riding and using the asteroid after capture are discussed. The hitchhiker uses momentum transfer only. The beachcomber, the caveman, the swinger, the prospector, and the rock wrecker also take advantage of raw asteroidal materials. The chemist and the hijacker go further, they process the asteroid into propellant. Or, an 'asteroid railway system' could evolve with each hijacked asteroid becoming a scheduled train. Travelers could board the space railway system assured that water, oxygen, and propellants await them.

Willoughby, Alan J.↗
NASA NTRS2000

Hypergolic Propellant Safety Course

Under the sponsorship of the NASA Safety Training Center at the Johnson Space Center, a hypergolic propellant safety course has been developed. This is a 2-day course on guidelines for hypergolic propellant system design, materials selection, operations, storage, and transportation. Recognizing that numerous fuels and oxidizers can be hypergolic, this course is specific to the hydrazine family of fuels and nitrogen tetroxide and its variants. The objectives of the course are to enable the student to identify and evaluate the hazards of hypergolic propellants, and to understand the methods for controlling those hazards and responding to emergencies. The course covers properties and hazards of the hydrazines and oxidizers; design and operations in hypergolic facilities; materials selection for use in hypergol systems; storage vessels, piping, and component considerations; hypergol detection; fire fighting practices; operating and transportation principles and procedures; and emergency practices and considerations. A hazards analysis methodology is presented. Numerous references are provided and the applicability of certain regulatory documents is discussed. A brief overview of other propellants, including hydrogen peroxide, is given at the end of the course.

Rathgeber, Kurt A.↗
NASA NTRS2001

Learning Styles of Pilots Currently Qualified in United States Air Force Aircraft

Kolb's Learning Style Inventory was used to identify the predominant learning styles of pilots currently qualified in United States Air Force aircraft. The results indicate that these pilots show a significant preference for facts and things over people and feelings. By understanding the preferred learning styles of the target population, course material can be developed that take advantage of the strengths of these learning styles. This information can be especially useful in the future design of cockpit resource management training. The training program can be developed to demonstrate both that there are different learning styles and that it is possible to take advantage of the relative strengths of each of these learning styles.

Kanske, Craig A.↗
NASA NTRS2016

Automated Segmentation and Classification of Coral using Fluid Lensing from Unmanned Airborne Platforms

In recent years, there has been a growing interest among biologists in monitoring the short and long term health of the world's coral reefs. The environmental impact of climate change poses a growing threat to these biologically diverse and fragile ecosystems, prompting scientists to use remote sensing platforms and computer vision algorithms to analyze shallow marine systems. In this study, we present a novel method for performing coral segmentation and classification from aerial data collected from small unmanned aerial vehicles (sUAV). Our method uses Fluid Lensing algorithms to remove and exploit strong optical distortions created along the air-fluid boundary to produce cm-scale resolution imagery of the ocean floor at depths up to 5 meters. A 3D model of the reef is reconstructed using structure from motion (SFM) algorithms, and the associated depth information is combined with multidimensional maximum a posteriori (MAP) estimation to separate organic from inorganic material and classify coral morphologies in the Fluid-Lensed transects. In this study, MAP estimation is performed using a set of manually classified 100 x 100 pixel training images to determine the most probable coral classification within an interrogated region of interest. Aerial footage of a coral reef was captured off the coast of American Samoa and used to test our proposed method. 90 x 20 meter transects of the Samoan coastline undergo automated classification and are manually segmented by a marine biologist for comparison, leading to success rates as high as 85%. This method has broad applications for coastal remote sensing, and will provide marine biologists access to large swaths of high resolution, segmented coral imagery.

algorithms segments classifications↗
NASA NTRS2015

Automated Segmentation and Classification of Coral Using Fluid Lensing from Unmanned Airborne Platforms

In recent years, there has been a growing interest among biologists in monitoring the short and long term health of the worlds coral reefs. The environmental impact of climate change poses a growing threat to these biologically diverse and fragile ecosystems, prompting scientists to use remote sensing platforms and computer vision algorithms to analyze shallow marine systems. In this study, we present a novel method for performing coral segmentation and classification from aerial data collected from small unmanned aerial vehicles (sUAV). Our method uses Fluid Lensing algorithms to remove and exploit strong optical distortions created along the air-fluid boundary to produce cm-scale resolution imagery of the ocean floor at depths up to 5 meters. A 3D model of the reef is reconstructed using structure from motion (SFM) algorithms, and the associated depth information is combined with multidimensional maximum a posteriori (MAP) estimation to separate organic from inorganic material and classify coral morphologies in the Fluid-Lensed transects. In this study, MAP estimation is performed using a set of manually classified 100 x 100 pixel training images to determine the most probable coral classification within an interrogated region of interest. Aerial footage of a coral reef was captured off the coast of American Samoa and used to test our proposed method. 90 x 20 meter transects of the Samoan coastline undergo automated classification and are manually segmented by a marine biologist for comparison, leading to success rates as high as 85. This method has broad applications for coastal remote sensing, and will provide marine biologists access to large swaths of high resolution, segmented coral imagery.

algorithms segments classifications↗
NASA NTRS1991

Momentum harvesting techniques for solar system travel

Astronomers are lately estimating there are 400,000 earth visiting asteroids larger than 100 meters in diameter. These asteroids are uniquely accessible sources of building materials, propellants, oxygen, water, and minerals. They also constitute a huge momentum reserve, potentially usable for travel throughout the solar system. To use this momentum, these stealthy objects must be tracked and the ability to extract the desired momentum obtained. Momentum harvesting by momentum transfer from asteroid to spacecraft, and by using the momentum of the extraterrestrial material to help deliver itself to its destination is discussed. The purpose is neither to quantify nor justify the momentum exchange processes, but to stimulate collective imaginations with some intriguing possibilities which emerge when momentum as well as material is considered. A net and tether concept is the suggested means of asteroid capture, the basic momentum exchange process. The energy damping characteristics of the tether determines the velocity mismatch that can be tolerated, and hence the amount of momentum that can be harvested per capture. As the tether plays out of its reel, drag on the tether steadily accelerates the spacecraft and dilutes, in time, the would-be collision. A variety of concepts for riding and using asteroids after capture are introduced. The hitchhiker uses momentum transfer only. The beachcomber, the caveman, the swinger, the prospector, and the rock wrecker also take advantage of raw asteroid materials. The chemist and the hijacker go further, they process the asteroid into propellants. Or, an asteroid railway system could be constructed with each hijacked asteroid becoming a scheduled train. Travelers could board this space railway system assured that water, oxygen propellants, and shielding await them. Austere space travel could give way to comforts, with a speed and economy impossible without nature's gift of earth visiting asteroids.

Willoughby, Alan J.↗
NASA NTRS1992

Application of neural networks to prediction of advanced composite structures mechanical response and behavior

Two types of neural networks were used to evaluate acousto-ultrasonic (AU) data for material characterization and mechanical reponse prediction. The neural networks included a simple feedforward network (backpropagation) and a radial basis functions network. Comparisons of results in terms of accuracy and training time are given. Acousto-ultrasonic (AU) measurements were performed on a series of tensile specimens composed of eight laminated layers of continuous, SiC fiber reinforced Ti-15-3 matrix. The frequency spectrum was dominated by frequencies of longitudinal wave resonance through the thickness of the specimen at the sending transducer. The magnitude of the frequency spectrum of the AU signal was used for calculating a stress-wave factor based on integrating the spectral distribution function and used for comparison with neural networks results.

Cios, K. J.↗
NASA NTRS1998

Take Off! Aeronautics and Aviation Science: Careers and Opportunities

Funded by National Aeronautic and Space Administration's High Performance Computing and Communications/ Learning Technologies Project (HPCC/LTP) Cooperative Agreement, Aeronautics and aviation Science: Careers and Opportunities was operative from July 1995 through July 1998. This project operated as a collaboration with Massachusetts Corporation for Educational Telecommunications, the Federal Aviation Administration, Bridgewater State College and four targeted "core sites" in the greater Boston area: Dorchester, Malden, East Boston and Randolph. In its first and second years, a video series with a participatory website on aeronautics and aviation science was developed and broadcast via "live, interactive" satellite feed. Accompanying teacher and student supplementary instructional materials for grades 6-12 were produced and disseminated by the Massachusetts Corporation for Educational Telecommunications (MCET). In year three, the project team redesigned the website, edited 14 videos to a five part thematic unit, and developed a teacher's guide to the video and web materials supplement for MAC and PC platforms, aligned with national standards. In the MCET grant application it states that project Take Off! in its initial phase would recruit and train teachers at "core" sites in the greater Boston area, as well as opening participation to other on-line users of MCET's satellite feeds. "Core site" classrooms would become equipped so that teachers and students might become engaged in an interactive format which aimed at not only involving the students during the "live" broadcast of the instructional video series, but which would encourage participation in electronic information gathering and sharing among participants. As a Take Off! project goal, four schools with a higher than average proportion of minority and underrepresented youth were invited to become involved with the project to give these students the opportunity to consider career exploration and development in the field of science aviation and aeronautics. The four sites chosen to participate in this project were East Boston High School, Dorchester High School, Randolph Junior-Senior High School and Malden High School. In year 3 Dorchester was unable to continue to fully participate and exited out. Danvers was added to the "core site" list in year 3.

Source record↗
NASA NTRS2002

Fatigue Crack Measurement in Composite Materials by Ultrasonic Methods

The nondestructive detection of intra-ply microcracking in unlined pressure vessels fabricated from composite materials is critical to ensuring mission success. Microcracking in composite structures due to combined fatigue and cryogenic thermal loading can be very troublesome to detect in-service and when it begins to link through the thickness can cause leakage and failure of the structure. These leaks may lead to loss of pressure/propellant, increased risk of explosion and possible cryo-pumping. The work presented herein develops a method and an instrument to locate and measure intraply fatigue cracking through the thickness of laminated composite material by means of correlation with ultrasonic resonance. Resonant ultrasound spectroscopy provides measurements which are, sensitive to both the microscopic and macroscopic properties of an object. Elastic moduli, acoustic attenuation, and geometry can all be probed. The approach is based on the premise of half-wavelength resonance. The method injects a broadband ultrasonic wave into the test structure using a swept frequency technique. This method provides dramatically increased energy input into the test article, as compared to conventional spike pulsed ultrasonics. This relative energy increase improves the ability to measure finer details in the materials character, such as micro-cracking and porosity. As the micro-crack density increases, more interactions occur with the higher frequency (small wavelength) components of the signal train causing the spectrum to shift toward lower frequencies. Preliminary experiments have verified a measurable effect on the resonance spectrum of the ultrasonic data to detect microcracking. Methods involving self organizing neural networks and other clustering algorithms show that the resonance ultrasound signatures from composites vary with the degree of microcracking and can be separated and identified.

Walker, James L.↗
NASA NTRS2015

On the Recovery Stress of a Ni50.3Ti29.7Hf20 High Temperature Shape Memory Alloy

Recovery stress in shape memory alloys (SMAs), also known as blocking stress, is an important property generally obtained during heating under a dimensional constraint as the material undergoes the martensitic phase transformation. This property has been instinctively utilized in most SMA shape-setting procedures, and has been used in numerous applications such as fastening and joining, rock splitting, safety release mechanisms, reinforced composites, medical devices, and many other applications. The stress generation is also relevant to actuator applications where jamming loads (e.g., in case the actuator gets stuck and is impeded from moving) need to be determined for proper hardware sizing. Recovery stresses in many SMA systems have been shown to reach stresses in the order of 800 MPa, achieved via thermo-mechanical training such as pre-straining, heat treatments or other factors. With the advent of high strength, high temperature SMAs, recovery stress data has been rarely probed, and there is no information pertinent to the magnitudes of these stresses. Thus, the purpose of this work is to investigate the recovery stress capability of a precipitation strengthened, Ni50.3Ti29.7Hf20 (at.) high temperature SMA in uniaxial tension and compression. This material has been shown to exhibit outstanding strength and stability during constant-stress, thermal cycling, but no data exists on constant-strain thermal cycling. Several training routines were implemented as part of this work including isothermal pre-straining, isobaric thermal cycling, and isothermal cyclic training routines. Regardless of the training method used, the recovery stress was characterized using constant-strain (strain-controlled condition) thermal cycling between the upper and lower cycle temperatures. Preliminary results indicate recovery stresses in excess of 1.5 GPa were obtained after a specific training routine. This stress magnitude is significantly higher than conventional NiTi stress generation capability.

Recovery Stress↗
NASA NTRS2016

Client-Side Data Processing and Training for Multispectral Imagery Applications in the GOES-R Era

RGB imagery can be created locally (i.e. client-side) from single band imagery already on the system with little impact given recommended change to texture cache in AWIPS II. Training/Reference material accessible to forecasters within their operational display system improves RGB interpretation and application as demonstrated at OPG. Application examples from experienced forecasters are needed to support the larger community use of RGB imagery and these can be integrated into the user's display system.

VIIRS↗
NASA NTRS2009

Tools Lighten Designs, Maintain Structural Integrity

Collier Research Corporation of Hampton, Virginia, licensed software developed at Langley Research Center to reduce design weight through the use of composite materials. The first license of NASA-developed software, it has now been used in everything from designing next-generation cargo containers, to airframes, rocket engines, ship hulls, and train bodies. The company now has sales of the NASA-derived software topping $4 million a year and has recently received several Small Business Innovation Research (SBIR) contracts to apply its software to nearly all aspects of the new Orion crew capsule design.

Source record↗
NASA NTRS2014

Ultrasonic/Sonic Jackhammer

The invention provides a novel jackhammer that utilizes ultrasonic and/or sonic vibrations as source of power. It is easy to operate and does not require extensive training, requiring substantially less physical capabilities from the user and thereby increasing the pool of potential operators. An important safety benefit is that it does not fracture resilient or compliant materials such as cable channels and conduits, tubing, plumbing, cabling and other embedded fixtures that may be encountered along the impact path. While the ultrasonic/sonic jackhammer of the invention is able to cut concrete and asphalt, it generates little back-propagated shocks or vibrations onto the mounting fixture, and can be operated from an automatic platform or robotic system. PNEUMATICS; ULTRASONICS; IMPACTORS; DRILLING; HAMMERS BRITTLE MATERIALS; DRILL BITS; PROTOTYPES; VIBRATION

Bar-Cohen, Yoseph↗
NASA NTRSDate not supplied

Towards Autonomous Lunar Resource Excavation via Reinforcement Learning

To continue on a sustainable and flexible path, NASA needs to address the challenge of collecting and moving large amounts of regolith at the destination. NASA’s Regolith Advanced Surface Systems Operations Robot (RASSOR) is principally designed to mine and deliver regolith for In-Situ Resource Utilization (ISRU) processing. RASSOR’s design enables it to efficiently collect and deposit regolith, return collected material for processing, and myriad related ISRU activities. To reliably perform these operations on the lunar surface, RASSOR software and sensory systems need to be robust and maximize the information extracted from a reduced sensor payload. Herein, we present preliminary findings from the Intelligent Capabilities Enhanced RASSOR project. We created reduced-order simulation environments to develop autonomous trenching controllers via reinforcement learning and prototype state estimation architectures. The goal of reinforcement learning is for an agent to learn a policy (task strategy) through interactions with an environment. When the agent performs an action, a change occurs in environment state and a numerical reward is received which informs the agent whether the action performed was good or not. Since reinforcement learning algorithms learn through trial-and-error, a simulation is a desirable first environment for development and learning. We developed two simulations, the first is a 2D excavation simulation developed to facilitate parameter selection, and a 3D simulation developed using a game physics engine, to simulate simplified soil interactions and increase the fidelity of the dynamic models of the robotic agents. The development of this 3D simulation has enabled the training of additional sensing capabilities and research both at the granular mechanics and operations levels. We experimented with various virtual sensor payloads to identify a combination that enabled efficient excavation operation and learning. Our reward function is based on how much material is excavated per step. A penalty is also received for leaving the dig site and to smooth the acceleration of the drum arms. We implemented pseudo time-of-flight sensors to report distance from each drum to ground and the height above ground which was found to be more efficient than existing solutions. Our findings suggest that reinforcement learning for autonomous operations has learned viable trenching strategies within 3000 training episodes in our simplified 2D environment and helped identify desirable sensing capabilities, arrangements, and considerations such as the positioning of time-of-flight sensors. Future work includes expanding our simulation to more complex environments and scenarios, and transfer learning from simulation to RASSOR 2.0 hardware for deployment in the Regolith Test Bin at NASA's Kennedy Space Center.

rassor↗
NASA NTRSDate not supplied

Variance Decomposition of MEDLI2 Reconstructed Heating Using Neural Networks

The Mars Entry, Descent, and Landing Instrumentation (MEDLI2) sensor suite collected data during entry of the Mars 2020 Perseverance rover into Mars’ atmosphere. This suite included a network of MEDLI2 Instrumented Sensor Plugs (MISPs). Each MISP was comprised of a cylinder made of Thermal Protection System (TPS) material with 1-3 embedded thermocouples (TCs), and it was flush mounted into the heatshield or backshell. Data from these in-depth TCs were used to reconstruct the aeroheating environment of the vehicle throughout entry. Surface heating was posed as an inverse problem, with the goal of estimating the surface heating by minimizing an objective function of the difference between MISP temperature measurements during flight and the temperature predictions derived from the Fully Implicit Ablation and Thermal response (FIAT) program. Given an aerothermal environment, FIAT calculates the material response and provides in-depth temperatures throughout the TPS material. To achieve the reverse, an internal tool called FIAT_Opt runs through multiple different environments until the output temperature at the TC depth closely matches the flight data. 95% confidence intervals on the reconstructed surface heating were obtained using Monte Carlo analysis, in which uncertainties in the thermocouple depth and the TPS material properties (e.g., density, thermal conductivity, heat capacity, emissivity) based on flight-lot material testing were included. A variance decomposition method using Sobol indices was employed to assess the sensitivity of the reconstructed peak heating to the TC placement and material property uncertainties. Variance decomposition was found to require tens of thousands of FIAT_Opt runs in order for the Sobol indices to converge. With a single FIAT_Opt run taking on the order of 40 minutes, the required number of computations would take months to complete, even if using multiple CPUs. To mitigate this problem, three machine learning models (ridge regression with cross-validation, random forest regression, and a deep neural network) were trained and tested using the 2000 Monte Carlo runs that were already completed. A subset of 1600 runs were used to train the model (i.e., training set), while the remaining 400 runs were used as the test set. The predictions from the deep neural network (DNN) on the test set showed nearly perfect agreement to the actual values computed with FIAT_Opt (R2 > 0.99). Using the DNN as a surrogate model, the variance decomposition using 50,000 runs was completed within minutes. The resulting Sobol indices showed that the reconstructed peak surface heating was most sensitive to the uncertainties in the thermal conductivity (ST = 0.37) and heat capacity (ST = 0.26). This method can be leveraged to provide requirements for material property measurements needed to improve the accuracy of surface heating prediction and ultimately lead to the reduction of design margins in the future. This presentation will include background on the MEDLI2 suite; the method used for inverse heating estimation; the way that material property uncertainties were accounted for using Monte Carlo analysis; a brief background on variance decomposition; the motivation for using machine learning in this context; how a neural network was trained on the data to enable variance decomposition in a fraction of the time; and the variance decomposition results for one of the MISPs.

Hannah Alpert↗
NASA NTRS1972

Skylab Saturn 1B flight manual

A Saturn 1B Flight Manual provides launch vehicle systems descriptions and predicted performance data for the Skylab missions. Vehicle SL-2 (SA-206) is the baseline for this manual; but, as a result of the great similarity, the material is representative of SL-3 and SL-4 launch vehicles, also. The Flight Manual is not a control document but is intended primarily as an aid to astronauts who are training for Skylab missions. In order to provide a comprehensive reference for that purpose, the manual also contains descriptions of the ground support interfaces, prelaunch operations, and emergency procedures. Mission variables and constraints are summarized, and mission control monitoring and data flow during launch preparation and flight are discussed.

Source record↗
NASA NTRS1982

Near surface observations

Learning objectives include: (1) developing an understanding of the implications of the term "near surface observations"; (2) associating the appearance of large ground features as seen in satellite imagery with their appearance as seen from the ground; (3) grasping criteria and procedures for selecting training sites on the ground for use in supervised classification; (4) running through an example of training site selection; (5) becoming familiar with several methods of accuracy assessment; (6) becoming aware of the approach and value of making supporting measurements of the spectral and physical properties of materials on the ground and from aircraft; (7) taking note of the different types of instruments used in making specific ground measurements; and (8) appreciating the rationale underlying laboratory and field studies on or near the Earth's surface for the purpose of developing new sensor systems.

Source record↗